Unscented extended Kalman filter for target tracking

被引：26
|
作者：
Liu, Changyun [1 ,2 ]
Shui, Penglang [1 ]
Li, Song [2 ]
机构：
[1] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
[2] AF Engn Univ, Missile Coll, Sanyuan 713800, Peoples R China
来源：
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2011年 / 22卷 / 02期
关键词：
unscented transformation (UT); extended Kalman filter (EKF); unscented extended Kalman filter (UEKF); unscented Kalman filter (UKF); nonliearity; PARTICLE FILTER;
D O I：
10.3969/j.issn.1004-4132.2011.02.002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new method of unscented extended Kalman filter (UEKF) for nonlinear system is presented. This new method is a combination of the unscented transformation and the extended Kalman filter (EKF). The extended Kalman filter is similar to that in a conventional EKF. However, in every running step of the EKF the unscented transformation is running, the deterministic sample is caught by unscented transformation, then posterior mean of non-linearity is caught by propagating, but the posterior covariance of nonlinearity is caught by linearizing. The accuracy of new method is a little better than that of the unscented Kalman filter (UKF), however, the computational time of the UEKF is much less than that of the UKF.
引用
收藏
页码：188 / 192
页数：5
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